MAGA: A Supervised Method to Detect Motifs From Annotated Groups in Alignments

Multiple sequence alignments are usually phylogenetically driven. They are studied in the framework of evolution. But sometimes, it is interesting to study residue conservation at positions unconstrained by evolutionary rules. We present a supervised method to access a layer of information difficult...

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Detalles Bibliográficos
Autores principales: Mier, Pablo, Andrade-Navarro, Miguel A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Methods and Protocols
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218316/
https://www.ncbi.nlm.nih.gov/pubmed/32425492
http://dx.doi.org/10.1177/1176934320916199
Descripción
Sumario:Multiple sequence alignments are usually phylogenetically driven. They are studied in the framework of evolution. But sometimes, it is interesting to study residue conservation at positions unconstrained by evolutionary rules. We present a supervised method to access a layer of information difficult to appreciate visually when many protein sequences are aligned. This new tool (MAGA; http://cbdm-01.zdv.uni-mainz.de/~munoz/maga/) locates positions in multiple sequence alignments differentially conserved in manually defined groups of sequences.

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